What are The 3 Layers of the Ignorance Graph Analysis?
Consensus Mapping, Gap Identification, and Entity Positioning: The Ignorance Graph analysis operates across three sequential layers. Each layer builds on the previous one. The output of Layer 3 is only as precise as the quality of the analysis in Layers 1 and 2.
Layer 1 — Consensus Mapping
What does the existing knowledge system say about this domain?
Layer 1 maps the current state of SERP consensus for the target domain with precision. This is not a competitor audit — it is an examination of the result set as a collective object. The goal is to identify: the minimum viable consensus (what all results share), the dominant framing (what all results assume), and the exact boundary of established knowledge.
Layer 1 output: a precise map of what is established, what vocabulary is canonical, and where the consensus ends.
Layer 2 — Gap Identification
What does the existing knowledge system not say — and what should it?
Layer 2 operates at the boundary defined by Layer 1. It examines the negative space: the concepts implied by the consensus that the consensus doesn’t define, the questions that every result skirts, the vocabulary that practitioners use but no indexed source authoritatively defines, the adjacent territory that the consensus consistently leaves unaddressed.
Layer 2 output: a ranked map of information gaps, ordered by gap-maximum value — the ratio of implied demand to depth of absence. Each gap on the map is a candidate for knowledge positioning.
Layer 3 — Entity Positioning
How does this gap become an entity in the knowledge graph?
Layer 3 translates the gap map into a deployable architecture. For each high-value gap, it specifies: the precise definition of the concept, the schema.org DefinedTerm structure required for entity recognition, the internal linking relationships that embed the new entity in the existing knowledge structure, and the external reference requirements that confirm the entity to the knowledge graph.
Layer 3 output: a complete entity architecture — not content in the standard sense, but knowledge infrastructure designed to function as a knowledge graph node from day one of publication.
The relationship between the 3 layers
The 3 layers cannot be shortcut. A gap identified without rigorous consensus mapping will often be a gap that already has an answer — just not in the obvious place. An entity positioned without precise definition will fail to achieve entity disambiguation. The value of the methodology is in the rigor of each layer, not in the speed of traversing them.